Data Science and Engineering

Scope & Guideline

Advancing the frontiers of data and technology.

Introduction

Delve into the academic richness of Data Science and Engineering with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN2364-1185
PublisherSPRINGERNATURE
Support Open AccessYes
CountryGermany
TypeJournal
Convergefrom 2016 to 2024
AbbreviationDATA SCI ENG / Data Sci. Eng.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressCAMPUS, 4 CRINAN ST, LONDON N1 9XW, ENGLAND

Aims and Scopes

The journal 'Data Science and Engineering' primarily focuses on the intersection of data science and engineering practices, exploring innovative methodologies and applications that leverage data for solving complex real-world problems. Its core areas encompass a variety of topics, with a consistent emphasis on advanced computational techniques, data-driven decision-making, and the integration of emerging technologies.
  1. Data Mining and Analysis:
    The journal emphasizes research in data mining techniques, including efficient algorithms for extracting insights from large datasets, anomaly detection, and classification methods.
  2. Graph and Network Analysis:
    A significant focus is on the application of graph theory and network analysis to various domains, including social networks, recommendation systems, and complex systems modeling.
  3. Machine Learning and Artificial Intelligence:
    The journal publishes works that advance machine learning methodologies, including deep learning, reinforcement learning, and their applications in diverse fields such as healthcare, transportation, and finance.
  4. Blockchain and Federated Learning:
    Research exploring the integration of blockchain technology with machine learning frameworks, particularly federated learning, is a key area of interest, emphasizing privacy-preserving data processing.
  5. Spatial-Temporal Data Processing:
    The journal covers methodologies for analyzing spatial-temporal data, crucial for applications in urban planning, traffic forecasting, and environmental monitoring.
  6. Recommendation Systems:
    A core area involves developing novel recommendation algorithms that utilize user behavior and preferences, often leveraging advanced techniques such as graph neural networks and contrastive learning.
Recent publications in 'Data Science and Engineering' reveal several emerging themes that are gaining traction, indicative of the journal's responsiveness to the latest technological advancements and societal needs.
  1. Federated Learning and Privacy-Preserving Techniques:
    There is a notable increase in research focused on federated learning and privacy-preserving methods, reflecting growing concerns over data privacy and the need for secure distributed learning frameworks.
  2. Graph Neural Networks and Their Applications:
    The rise of graph neural networks in various applications, including social recommendation and anomaly detection, highlights an emerging trend that emphasizes the importance of relational data in modern data science.
  3. Integration of AI with IoT (AIoT):
    Papers exploring the intersection of artificial intelligence and the Internet of Things (IoT) are on the rise, particularly in applications like smart cities and infrastructure maintenance, showcasing the relevance of data science in real-time sensing and automation.
  4. Explainable AI (XAI):
    The growing emphasis on explainability in AI systems is reflected in increasing publications addressing how to make machine learning models more interpretable and accountable, which is essential for user trust and regulatory compliance.
  5. Multi-modal and Cross-domain Learning:
    Research that involves learning from multiple data modalities and across different domains is gaining prominence, indicating a trend towards more holistic approaches to data analysis and model training.

Declining or Waning

While 'Data Science and Engineering' has a robust focus on various contemporary topics, certain themes appear to be declining in prominence. This shift may reflect evolving research interests and technological advancements within the field.
  1. Traditional Statistical Methods:
    There seems to be a waning interest in conventional statistical analysis techniques, as the focus shifts towards more advanced machine learning and data mining methods.
  2. Basic Data Structures and Algorithms:
    Papers centered on fundamental data structures and algorithms are becoming less frequent, indicating a movement towards more complex applications and hybrid approaches involving multiple methodologies.
  3. Classic Database Management Systems (DBMS):
    Research that solely focuses on traditional DBMS without the integration of modern data processing techniques (like big data or NoSQL systems) appears to be declining, as the field moves towards more innovative data architectures.

Similar Journals

Jordanian Journal of Computers and Information Technology

Fostering Global Dialogue in Computer Science and IT
Publisher: Princess Sumaya Univ & SRSFISSN: 2413-9351Frequency: 4 issues/year

Jordanian Journal of Computers and Information Technology, published by Princess Sumaya University and SRSF, stands as a significant platform for scholarly research in the realm of computer science, particularly in topics related to emerging technologies and information systems. With its Open Access model initiated in 2015, the journal facilitates global access to high-quality research findings, embodying the principles of knowledge sharing and academic collaboration. The journal's ranking in the Q3 category of Computer Science (miscellaneous) and its placement in the 54th percentile of Scopus' General Computer Science rankings underscore its growing reputation among researchers and professionals alike. Situated in Amman, Jordan, the journal actively contributes to the regional and international discourse on computing methodologies, applications, and innovations, making it an indispensable resource for scholars seeking to advance their understanding and engage with contemporary issues in technology.

Science China-Information Sciences

Pioneering Knowledge in the Evolving Landscape of Information Sciences.
Publisher: SCIENCE PRESSISSN: 1674-733XFrequency: 1 issue/year

Science China-Information Sciences is a prestigious academic journal published by SCIENCE PRESS, dedicated to advancing knowledge in the field of information sciences and computer science. Established in China, the journal has gained a remarkable reputation, with a 2023 category quartile ranking of Q1 in Computer Science (miscellaneous) and an impressive Scopus rank of #16 out of 232 in General Computer Science, positioning it within the 93rd percentile. The journal embraces a broad spectrum of topics, from theoretical frameworks to practical applications, providing a platform for researchers, professionals, and students to disseminate their findings and engage with the latest advancements in the field. With open access options available, Science China-Information Sciences ensures that innovative research is accessible to a global audience, fostering collaboration and interdisciplinary dialogue. The journal not only reflects the evolving landscape of information sciences but also plays a pivotal role in shaping future research directions.

JOURNAL OF INTELLIGENT INFORMATION SYSTEMS

Shaping the Future of Intelligent Systems Research
Publisher: SPRINGERISSN: 0925-9902Frequency: 6 issues/year

The Journal of Intelligent Information Systems, published by Springer since 1992, is a premier academic journal that offers a multidisciplinary platform in the fields of Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, and Software. With an impressive impact reflected in its 2023 Q2 category rankings across multiple domains and a commendable standing in the Scopus Rankings—ranking #84 in Computer Networks and Communications and #101 in Artificial Intelligence—the journal is recognized for its contribution to advancing knowledge and innovation. Although it is not an open-access journal, its accessibility through institutional subscriptions ensures that a wide range of researchers, professionals, and students can engage with high-quality, peer-reviewed research that addresses the latest advancements and trends in intelligent systems. For over three decades, this journal has effectively bridged gaps between academia and industry, making it a vital resource for those aiming to push boundaries in intelligent information systems.

International Journal of Intelligent Information Technologies

Empowering Insights through Innovative Information Technologies.
Publisher: IGI GLOBALISSN: 1548-3657Frequency: 4 issues/year

Founded in 2005, the International Journal of Intelligent Information Technologies serves as a pivotal platform for the dissemination of cutting-edge research in the fields of decision sciences and information systems. Published by IGI Global, this journal is dedicated to advancing the understanding of intelligent systems, data analytics, and technological innovations that drive modern decision-making processes. With an ISSN of 1548-3657 and an E-ISSN of 1548-3665, the journal is indexed strategically to ensure visibility among academia and industry professionals. Although it currently holds a ranking in the Q4 quartile of both decision sciences and information systems categories in 2023, it stands out for its comprehensive investigations into best practices and emerging trends in intelligent information technologies. It aims to provide readers with rigorous, peer-reviewed articles that offer practical insights and theoretical frameworks to facilitate informed decision-making in an increasingly data-driven world. Its commitment to quality research makes it an invaluable resource for researchers, professionals, and students alike who are eager to explore new dimensions of technology-assisted decision-making.

APPLIED INTELLIGENCE

Connecting research and practice in the world of AI.
Publisher: SPRINGERISSN: 0924-669XFrequency: 12 issues/year

Applied Intelligence is a prominent peer-reviewed journal that has been instrumental in advancing the field of Artificial Intelligence since its inception in 1991. Published by Springer, a reputable name in academic publishing, the journal focuses on the innovative applications of intelligent systems, algorithms, and methodologies across various disciplines. With an impressive Q2 ranking in the Artificial Intelligence category for 2023, and a Scopus rank of #117 out of 350 in its field, Applied Intelligence is recognized for its significant contributions and rigorous standards. The journal is accessed primarily through subscription, ensuring that high-quality research reaches the academic community and industry professionals alike. Its commitment to disseminating cutting-edge research makes it an invaluable resource for researchers, practitioners, and students interested in the practical implications of AI advancements. Join a community dedicated to exploring the transformative power of artificial intelligence and stay ahead in this ever-evolving field!

Big Data Mining and Analytics

Shaping Tomorrow's Technologies with Big Data Insights
Publisher: TSINGHUA UNIV PRESSISSN: Frequency: 4 issues/year

Big Data Mining and Analytics, published by TSINGHUA UNIVERSITY PRESS, stands at the forefront of interdisciplinary research in the fields of Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, and Information Systems. With an impressive Q1 ranking in multiple categories as of 2023, this journal serves as a critical platform for researchers and professionals eager to explore innovative techniques and methodologies related to big data analytics. Since its transition to Open Access in 2018, Big Data Mining and Analytics has aimed to increase the visibility and accessibility of its cutting-edge research, making permanent strides in the global academic landscape. Housed in Beijing, China, and actively embracing the converged years from 2018 to 2024, the journal aims to cultivate a rich discourse on emerging trends and applications, ensuring its relevance in a rapidly evolving technological environment. Join a vibrant community of scholars dedicated to advancing the frontiers of knowledge in big data.

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES

Unraveling complexities with cutting-edge optimization methods.
Publisher: TARU PUBLICATIONSISSN: 0252-2667Frequency: 8 issues/year

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, published by TARU PUBLICATIONS, is a vital platform for researchers and practitioners in the field of information science and optimization techniques. With a focus on the application of mathematical and computational methods to solve complex problems in various domains, this journal aims to advance knowledge and encourage innovative thinking. The journal's ISSN is 0252-2667 and the E-ISSN is 2169-0103. Although currently not Open Access, it strives to provide high-quality research that significantly contributes to the industry. With a commitment to rigor and excellence, the JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES is essential for anyone dedicated to enhancing their understanding and application of optimization methodologies in an ever-evolving technological landscape.

INFORMATION SCIENCES

Fostering Excellence in Information Sciences
Publisher: ELSEVIER SCIENCE INCISSN: 0020-0255Frequency: 36 issues/year

INFORMATION SCIENCES, published by Elsevier Science Inc, is a premier peer-reviewed journal that has become instrumental in advancing the field of information science since its inception in 1968. With an impressive array of quartile rankings in 2023, including Q1 in Artificial Intelligence, Computer Science Applications, Control and Systems Engineering, Information Systems and Management, Software, and Theoretical Computer Science, this journal serves as a vital resource for researchers and professionals looking to explore cutting-edge theories and practical applications within these domains. The journal is indexed extensively, with notable Scopus rankings, reflecting its significance and influence in the academic community—ranked 6th in Theoretical Computer Science and 10th in Information Systems and Management, among others. Although it does not currently offer an open-access option, the depth of research published within INFORMATION SCIENCES ensures that it remains a key reference point for advancing academic inquiry and addressing complex challenges in the information landscape.

Statistical Analysis and Data Mining

Transforming Data into Actionable Insights
Publisher: WILEYISSN: 1932-1864Frequency: 6 issues/year

Statistical Analysis and Data Mining is a leading journal published by WILEY, dedicated to exploring the latest advancements in statistical methods and data mining techniques. With an ISSN of 1932-1864 and an E-ISSN of 1932-1872, this journal serves as a significant platform for researchers and professionals in statistical analysis, computer science applications, and information systems. Covering a wide range of topics from innovative analytical methodologies to emerging data mining algorithms, the journal aims to disseminate high-quality research that contributes to the evolving landscape of data science. Ranked in the Q2 category for the fields of Analysis, Computer Science Applications, and Information Systems in 2023, it emphasizes its relevance and impact within academia. While it offers limited Open Access options, the insights shared in this publication are integral for those wishing to stay ahead in fast-paced research and data-driven industries. Since its inception in 2008 and continuing through 2024, Statistical Analysis and Data Mining invites submissions that reflect rigorous empirical research coupled with practical implications, making it a vital resource for the academic community.

ADVANCED ENGINEERING INFORMATICS

Empowering Innovation Through Open Access Research
Publisher: ELSEVIER SCI LTDISSN: 1474-0346Frequency: 4 issues/year

ADVANCED ENGINEERING INFORMATICS is a prestigious journal published by Elsevier Science Ltd, dedicated to the interdisciplinary fields of Artificial Intelligence and Information Systems. Established in 2002, this journal serves as a vital platform for researchers and practitioners to disseminate groundbreaking insights and innovations that shape the future of engineering and technological integration. With an impressive impact factor and ranked in the Q1 category for both Artificial Intelligence and Information Systems in 2023, it holds a prominent position, with Scopus rankings placing it in the 92nd percentile among 394 journals in Computer Science Information Systems and the 87th percentile among 350 journals in Computer Science Artificial Intelligence. ADVANCED ENGINEERING INFORMATICS embraces an Open Access model, ensuring that cutting-edge research is accessible to a global audience, fostering collaboration and development across academic and professional circles. The journal is committed to advancing knowledge and influencing practice, paving the way for the next generation of technologies that enhance engineering informatics.